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A new hybrid optimization technique based on antlion and grasshopper optimization algorithms

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Abstract

This paper proposes a new hybrid algorithm that merges the main features of two well-known metaheuristic algorithms; Grasshopper Optimization Algorithm (GOA) and Antlion Optimization (ALO) algorithm. ALO is strong in exploitation due to the mechanism of antlions in hunting other insects. On the other hand, the social forces in GOA represent the strong capability of exploration all over the search space. So, these features give the chance to combine ALO and GOA in one hybrid algorithm that significantly enhances the performance of both methods. The proposed hybrid algorithm is tested on 32 well-known benchmark test functions, 13 functions of the challenging CEC2015 functions, and two real problems in antenna array synthesis where the elements’ excitation amplitudes and phases are optimized to minimize the maximum sidelobe level and impose nulls at specific angles. Comparisons show that the proposed algorithm outperforms 18 well-known optimization methods, including ALO and GOA, in the majority of these tests, with huge differences in some of them, which prove the stability, robustness, and efficiency of the proposed method over other robust algorithms.

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Acknowledgements

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. The authors declare no conflict of interest in this research work.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, University of Oklahoma, Norman, 73071, USA

    Anas Atef Amaireh

  2. Telecommunications Engineering Department, Yarmouk University, P. O. Box 35, Irbid, 21163, Jordan

    Asem S. Al-Zoubi

  3. Electrical Engineering Department, Jordan University of Science and Technology, P. O. Box 3030, Irbid, 22110, Jordan

    Nihad I. Dib

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  1. Anas Atef Amaireh
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Appendix

Appendix

See Tables

Table 4 Unimodal test functions
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Table 5 Multimodal and composite functions
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Table 6 Results of unimodal benchmark functions
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Table 7 Results of multimodal and composite benchmark functions
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Table 8 CEC2015 benchmark test functions
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Table 9 The normalized results of CEC2015 functions
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Amaireh, A.A., Al-Zoubi, A.S. & Dib, N.I. A new hybrid optimization technique based on antlion and grasshopper optimization algorithms. Evol. Intel. 16, 1383–1422 (2023). https://doi.org/10.1007/s12065-022-00749-4

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